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Lung cancer is the leading reason behind cancer-related deaths within theworld. Early detection of lung nodules is vital for increasing the survivalrate of cancer patients. Traditionally, physicians should manually identify theworld suspected of getting carcinoma. When developing these detection systems,the arbitrariness of lung nodules' shape, size, and texture could be achallenge. Many studies showed the applied of computer vision algorithms toaccurate diagnosis and classification of lung nodules. A deep learningalgorithm called the VGG16 was developed during this paper to help medicalprofessionals diagnose and classify carcinoma nodules. VGG16 can classifymedical images of carcinoma in malignant, benign, and healthy patients. Thispaper showed that nodule detection using this single neural network had 92.08%sensitivity, 91% accuracy, and an AUC of 93%.

Using VGG16 Algorithms for classification of lung cancer in CT scans Image